With approximately **** million recreational visits in 2023, the Blue Ridge Parkway in North Carolina and Virginia was the most visited National Park Service site in the United States. Meanwhile, the Golden Gate National Recreation Area in California was the second most visited site in the country.

This dataset is used for the analysis in the publication entitled "Using data derived from cellular device locations to estimate visitation to natural areas: an application to the U.S. National Park system". It includes cell data purchased from Airsage Inc. at the monthly resolution for years 2018 and 2019 for 38 park units in the U.S. National Park system, corresponding monthly visitation obtained from the NPS Stats (https://irma.nps.gov/STATS/), and park attributes that are considered to affect the relationships between Cell and NPS data in the analysis.

Yellowstone National Park in the United States – the country’s oldest national park - attracted a total of approximately 4.5 million visitors in 2023. The park received over three million visitors annually since 2008 and reached its visitation peak in 2021.  U.S. National Park Service  Established in 1872 and located predominantly in Wyoming, Yellowstone remains one of the most popular national parks in the United States, ranking third in terms of visitor numbers in 2021. However, with over 14 million recreational park visits in 2021, the Great Smoky Mountains National Park, straddling the border between North Carolina and Tennessee, was by far the most visited national park in the country. All national parks in the U.S. are managed, protected and presented by the National Park Service, an agency of the U.S. federal government. There were approximately 92 million visitors to national parks in the U.S. in 2021. National parks and the hospitality industry Visitors to national parks are a valuable source of income to the United States economy. In 2021, national park visitors spent roughly seven billion U.S. dollars on lodging and four billion on restaurants and bars.

Annual visitor records were downloaded for each NPS unit within the study area (Visitor Use Statistics, NPS 2015). NPS [National Park Service]. 2015. NPS Stats: National Park Service visitor use statistics. National Park Service, Department of Agriculture, Washington D.C., USA.

In 2021, July was the busiest month for National Park Service sites in the United States. That month, national sites attracted about 1.3 million visitors per day, denoting a 25 percent increase in the average daily number of people going to sites over the same month in the previous year.

The region in the United States that had the highest National Park Service visitation was the Southeast, with approximately 73.7 million visitors in 2023. This region includes the famous Great Smoky Mountains. The second-most visited region was the Pacific West, home to Yosemite National Park.

The SWAN Visitor Use Monitoring dataset represents visitor use monitoring areas defined by the National Park Service (NPS) Alaska Region for commercial use authorization (CUA) reporting and Vital Signs Monitoring in a subset of NPS Southwest Alaska Network park units. To date, visitor use monitoring areas have been established for Alagnak Wild River, Aniakchak National Monument and Preserve, Katmai National Park & Preserve (NP&Pr), and Lake Clark NP&Pr. The area records contained in this dataset are intended to provide complete spatial coverage for each NPS park unit by representing visitor use locations with reported CUA visitation, as well as locations with potential for CUA visitation.

Understanding human use of public lands is essential for management of natural and cultural resources. However, compiling consistently reliable visitation data across large spatial and temporal scales and across different land managing entities is challenging. Cellular device locations have been demonstrated as a source to map human activity patterns and may offer a viable solution to overcome some of the challenges that traditional on-the-ground visitation counts face on public lands. Yet, large-scale applicability of human mobility data derived from cell phone device locations for estimating visitation counts to public lands remains unclear. This study aims to address this knowledge gap by examining the efficacy and limitations of using commercially available cellular data to estimate visitation to public lands. We used the United States’ National Park Service’s (NPS) 2018 and 2019 monthly visitor use counts as a ground-truth and developed visitation models using cellular device location-derived monthly visitor counts as a predictor variable. Other covariates, including park unit type, porousness, and park setting (i.e., urban vs. non-urban, iconic vs. local), were included in the model to examine the impact of park attributes on the relationship between NPS and cell phone-derived counts. We applied Pearson’s correlation and generalized linear mixed model with adjustment of month and accounting for potential clustering by the individual park units to evaluate the reliability of using cell data to estimate visitation counts. Of the 38 parks in our study, 20 parks had a correlation of greater than 0.8 between monthly NPS and cell data counts and 8 parks had a correlation of less than 0.5. Regression modeling showed that the cell data could explain a great amount of the variability (conditional R-squared = 0.96) of NPS counts. However, these relationships varied across parks, with better associations generally observed for iconic parks. While our study increased our confidence in using cell phone data to estimate visitation, we also became aware of some of the limitations and challenges which we present in the Discussion.

This dataset depicts the park visitor centers. The intended use of all data in the park's GIS library is to support diverse park activities including planning, management, maintenance, research, and interpretation.In September of 2015 this (point/line/polygon) layer was given the Point of Interest standard attributes and reviewed by BIBE for the purpose of updating visitor data for public use. These data were reviewed by BIBE using an ArcGIS Online feature service where the park edited and updated the geometry and attributes. These data were then reviewed by the Intermountain Region Geographic Resources Division.

This point dataset was created to show the visitor center locations in Rocky Mountain National Park. The point locations were extracted from the NPS FMSS. Edits were made by Glenn Hoffman at ROMO in November 2016 to incorporate the NPS Core Data Standard dated 08/10/2016.

The statistic depicts the number of visitors taking a study tour of the Fukushima Daiichi NPS from fiscal year 2011 to 2016. In fiscal year 2016, more than 10.6 thousand people joined a site tour of the Fukushima nuclear power plant, up from around 900 visitors in fiscal 2011.

Climate change will affect not only natural and cultural resources within protected areas but also tourism and visitation patterns. The U.S. National Park Service systematically collects data regarding its 270+ million annual recreation visits, and therefore provides an opportunity to examine how human visitation may respond to climate change from the tropics to the polar regions. To assess the relationship between climate and park visitation, we evaluated historical monthly mean air temperature and visitation data (1979–2013) at 340 parks and projected potential future visitation (2041–2060) based on two warming-climate scenarios and two visitation-growth scenarios. For the entire park system a third-order polynomial temperature model explained 69% of the variation in historical visitation trends. Visitation generally increased with increasing average monthly temperature, but decreased strongly with temperatures > 25°C. Linear to polynomial monthly temperature models also explained historical visitation at individual parks (R2 0.12-0.99, mean = 0.79, median = 0.87). Future visitation at almost all parks (95%) may change based on historical temperature, historical visitation, and future temperature projections. Warming-mediated increases in potential visitation are projected for most months in most parks (67–77% of months; range across future scenarios), resulting in future increases in total annual visits across the park system (8–23%) and expansion of the visitation season at individual parks (13–31 days). Although very warm months at some parks may see decreases in future visitation, this potential change represents a relatively small proportion of visitation across the national park system. A changing climate is likely to have cascading and complex effects on protected area visitation, management, and local economies. Results suggest that protected areas and neighboring communities that develop adaptation strategies for these changes may be able to both capitalize on opportunities and minimize detriment related to changing visitation.

The Integrated Resource Management Applications (IRMA) Portal provides easy access to National Park Service applications that manage and deliver resource information to parks, partners and the public.

From irma.nps.gov users can find and download reports, data sets, geospatial data, and park species lists. Users can also get information on park visitor numbers, park projects, and apply for a park research permit.

These data depict Road Segment Centerlines and attributes for roads that are managed and maintained by the National Park Service. Road data are used for many purposes including planning and management, mapping and condition assessment, routing and navigation, public information, emergency response, and research. A current, accurate representation of park roads is needed for national reporting and a variety of mapping requirements at all levels of the National Park Service and the general public. A National-level dataset allows the NPS to communicate a consistent and high-quality roads database to NPS staff, partners, visitors, and entities that produce maps and location-based services of park units. The collection, storage, and management of road-related data are important components of everyday business activities in many Federal and State land-managing agencies, road organizations, and businesses. From a management perspective, road data must often mesh closely with other types of infrastructure, resource, and facility enterprise data. For the public using paper maps, the internet, GPS or other instrumentation, standard data formats enable users to consistently and predictably identify specific trails and a core set of corresponding information. Today, digital road data are a necessity throughout a road data management life-cycle, from road planning through design, construction, operation, and maintenance. Automating, sharing, and leveraging road data through this widely accepted standard can provide a variety of important benefits: Efficiency – creating and gathering road data that are standardized and readily usable. Compatibility – compiling data from one project or discipline that can be compatible with other applications; Consistency – using the same standards, meshing data produced by one organization with that developed by another; Speed – hastening the availability of data through a reduction in duplicative efforts and lowered production costs (Applications can be developed more quickly and with more interoperability by using existing standards-compliant data); Conflict resolution – resolving conflicting road data more easily if compliant to the same standards; Reliability – improving the quality of shared road data by increasing the number of individuals who find and correct errors; and Reusability – allow maximum reuse across agencies and support objectives of EGovernment (E-Gov) initiatives and enterprise architecture.

Understanding human use of public lands is essential for management of natural and cultural resources. However, compiling consistently reliable visitation data across large spatial and temporal scales and across different land managing entities is challenging. Cellular device locations have been demonstrated as a source to map human activity patterns and may offer a viable solution to overcome some of the challenges that traditional on-the-ground visitation counts face on public lands. Yet, large-scale applicability of human mobility data derived from cell phone device locations for estimating visitation counts to public lands remains unclear. This study aims to address this knowledge gap by examining the efficacy and limitations of using commercially available cellular data to estimate visitation to public lands. We used the United States’ National Park Service’s (NPS) 2018 and 2019 monthly visitor use counts as a ground-truth and developed visitation models using cellular device location-derived monthly visitor counts as a predictor variable. Other covariates, including park unit type, porousness, and park setting (i.e., urban vs. non-urban, iconic vs. local), were included in the model to examine the impact of park attributes on the relationship between NPS and cell phone-derived counts. We applied Pearson’s correlation and generalized linear mixed model with adjustment of month and accounting for potential clustering by the individual park units to evaluate the reliability of using cell data to estimate visitation counts. Of the 38 parks in our study, 20 parks had a correlation of greater than 0.8 between monthly NPS and cell data counts and 8 parks had a correlation of less than 0.5. Regression modeling showed that the cell data could explain a great amount of the variability (conditional R-squared = 0.96) of NPS counts. However, these relationships varied across parks, with better associations generally observed for iconic parks. While our study increased our confidence in using cell phone data to estimate visitation, we also became aware of some of the limitations and challenges which we present in the Discussion.

In 2013 to mark the 175th anniversary of John Muir's birth CyArk in collaboration with Historic Environment Scotland and the National Park Service documented Muir's birthplace in Dunbar, Scotland and his home in Martinez, California.The project consisted of documentation through 3D data capture and high resolution digital photography, data registration and photographic processing, the development of measurable raster point-cloud image results, creation of educational and cultural tourism media for sharing the stories of the site. The John Muir National Historic Site is located in the San Francisco Bay Area, in Martinez, Contra Costa County, California. It preserves the 14-room Italianate Victorian mansion where the naturalist and writer John Muir lived, as well as a nearby 325-acre tract of native oak woodlands and grasslands historically owned by the Muir family. Muir was perhaps this country's most famous and influential naturalist. If it weren't for John Muir and his writings, we probably would not have Yosemite National Park as we know it today. He was also involved in the creation of the Grand Canyon, Kings Canyon, Petrified Forest, and Mt. Rainier National Parks. Additionally, his writings about Alaska led to further preservation of the landscape over time. Because of his influential writings and role in the creation of multiple parks, he is often called The Father of Our National Park System."" External Project Link: \N Additional Info Link:

National parks were the most visited type of park in the United States in 2023. Overall, 28 percent of recreational visits to national sites in the North American country were to national parks, whereas national monuments recorded just six percent of total visits that year.

Shuttle routes in SEKI, including the Big Trees transit introduced to Grant Grove area in 2015 and routes updated in 2022. Data are based on SEKI Roads feature class, with source information from Transportation and Division of Interpretation. These data do not show seasonal changes or represent any regular or unscheduled route changes. Schema changes occurred in 2022 to reflect different route planning and operation.

This data set contains continuous water level, specific conductance, and temperature measured in KAHO 1 (State Well No. 4061-001), KAHO 2 (State Well No. 4161-002), KAHO 3 (State Well No. 4161-001), and Aimakapa Fishpond (2-inch PVC monitoring pipe) by the National Park Service (NPS) and the U.S. Geological Survey (USGS) Pacific Island Water Science Center during the period 2007 to present. The wells are locally known as the Visitor Center Well, the Upper Kaloko Road Well, and the Lower Kaloko Road Well, respectively. These data were processed for quality assurance/quality control by the USGS. This data set also includes station documents (Station Analysis, Station Description, and Manuscript) prepared by the USGS for the periods when the NPS conducted data collection. The monitoring data in this data set can be viewed online at the external links provided in this reference.

Natural parks (NPs) have a primary role in supporting people’s welfare by maintaining natural and cultural resources. Various activities, such as those related to conservation of flora and fauna, forestry, agriculture and livestock, residential, and tourism, coexist within the boundaries of NPs. All these activities may contribute as a source or sink of carbon dioxide and, despite some NPs having started to promote their environmental services, there is currently a lack of information on their carbon footprint (CF). Although various international standards have provided guidelines to assess the CF of organizations, a lack of explicit formulation and procedure in these standards makes them difficult to apply, especially when the organizations to be evaluated embed a wide range of biological and anthropogenic activities. The framework proposed in this paper provides for the first time a holistic methodological approach to quantitatively and qualitatively estimate the annual greenhouse gas (GHG) emissions and removals occurring in NPs. The main data needed for the NP’s GHG inventory were directly collected on-site. The activity data and emissions factors as well as the methodologies involved were all referenced to their data sources, including the use of a biogeochemical model, IPCC equations, Ecoinvent database, and a literature review. This method highlighted that, by emitting 0.55 Mg CO2e ha−1 year−1, the NP generates an annual CF of about 3,300 Mg of CO2e. The agricultural activities with 43.4% of share showed the largest incidence, followed by wild fauna (17.8%), tourism (15.1%), and, to a lesser extent, all the other sectors considered in the assessment. On the other hand, when the annual soil and forest C sequestration rates were included in the balance, the NP contributes to sequester about 3.7 Mg CO2e ha−1 year−1, thus resulting in it being an important C-sink site (i.e., about 22,000 Mg CO2e year−1). By providing granular information on GHG emissions and carbon removals trend, the methodological approach involved in this study could help NPs in both planning effective mitigation strategies and supporting environmental certification processes. CF of NPs could increase tourists’ awareness of the important role that these protected natural areas have in climate change mitigation and adaptation.